Market watcher IDC estimates that corporate spending on compute and storage hardware for AI deployments increased by 37% in the first half of 2024, and predicts it will exceed $100 billion by 2028. However, concerns are growing around the energy consumption of AI infrastructure, with reports suggesting AI-driven datacenter energy demands could increase by 160% in the next two years. This could potentially impact datacenter expansion plans and investor enthusiasm.
Key takeaways:
- Organizations are grappling with the rising power consumption and energy costs associated with training and deploying advanced AI models, according to chief analyst Alastair Edwards at the Canalys Forum EMEA.
- While public cloud vendors are often the go-to for training AI workloads, the cost becomes unsustainable when it comes to deploying and scaling these models.
- As an alternative, some companies are turning to colocation and specialized hosting providers, with new business models such as GPU-as-a-service emerging.
- IDC estimates that corporates increased spending on compute and storage hardware for AI deployments by 37 percent in the first half of 2024, and forecasts that this will expand to top $100 billion by 2028.